{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "0_Datapreparation.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyPApZRKbKOiHjWIn8Q/pWoI"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "SaL0lwT-0Cml"
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib as mpl\n",
        "\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "\n",
        "import glob"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P6wmqozG0MSb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "daa706f5-af5a-4150-8b19-87104086e144"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wByRDeQm5QC7"
      },
      "source": [
        "# Select bus trip data and merge with weather information"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LGx-OTM86LBJ"
      },
      "source": [
        "#function to open temperature dataset\n",
        "def temp(path_tem =r'/content/drive/My Drive/Colab Notebooks/Thesis/temperature' ):\n",
        "  #path_tem =r'/content/drive/My Drive/Colab Notebooks/Thesis/temperature' # use your path\n",
        "  allFiles = glob.glob(path_tem + \"/*.txt\")\n",
        "\n",
        "  list_ = []\n",
        "  i=0\n",
        "\n",
        "\n",
        "  for file_ in allFiles:\n",
        "      df = pd.read_csv(file_, sep=';',skiprows=1,\n",
        "                        names = ['STATIONS_ID','MESS_DATUM','QN_8','R1','Precipitation','WRTR','eor'\n",
        "                                ])\n",
        "      #df['date'] = date_list[i]\n",
        "      #df['line'] = line_list[i]\n",
        "\n",
        "      #df = restructure_data(df)\n",
        "      list_.append(df)\n",
        "      i+=1\n",
        "\n",
        "  Ta_list = pd.concat(list_, axis = 0, ignore_index = True)\n",
        "  Ta_list = Ta_list.drop(['STATIONS_ID','QN_8','WRTR', 'eor'], axis=1)\n",
        "  Ta_list['date_time'] = pd.to_datetime(Ta_list.MESS_DATUM, format='%Y%m%d%H', errors='ignore')\n",
        "  Ta_list= Ta_list.groupby(['date_time'], as_index=False).mean()\n",
        "  Ta_list['Precipitation'] = np.ceil(Ta_list.Precipitation)\n",
        "  return Ta_list"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5K2S38jt5Plg"
      },
      "source": [
        "file_name = 112 # or 4\n",
        "\n",
        "if file_name == 112: #the whole year 2019\n",
        "  path = \"/content/drive/My Drive/Colab Notebooks/Thesis/IST_filter_Line28.csv\"\n",
        "  df = pd.read_csv(path)\n",
        "  df = df.drop(['index'], axis=1)\n",
        "  df['Ab_ZT_PLAN'] = df['Ab_ZT_PLAN'].astype('datetime64[ns]')\n",
        "  df['Ank_ZT_PLAN'] = df['Ank_ZT_PLAN'].astype('datetime64[ns]')\n",
        "  df['TagMean'] = df['Ab_ZT_PLAN']+(df['Ank_ZT_PLAN']-df['Ab_ZT_PLAN'])/2\n",
        "  df['TagRound'] = df['TagMean'].dt.round(\"H\")\n",
        "  df['TagRound'] = df['TagRound'].astype('datetime64[ns]')\n",
        "\n",
        "  Ta_list = temp()\n",
        "\n",
        "  dft_join = pd.merge(df, Ta_list, how='left', left_on=['TagRound'], right_on = ['date_time'])\n",
        "  dft_join = dft_join.drop('date_time', axis = 1)\n",
        "  \n",
        "  df_filter = dft_join.copy()\n",
        "elif file_name == 4: #only April\n",
        "  path = \"/content/drive/My Drive/Colab Notebooks/Thesis/IST_ECR_filter_0419.csv\"\n",
        "  df_filter = pd.read_csv(path)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EOqBWqHS2BRF"
      },
      "source": [
        "# **Having a quick look at the data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZtqhrxFb2rE-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "outputId": "8da83b3f-0e84-4ddd-f9d0-5ed4711c1bc2"
      },
      "source": [
        "#df_filter = df_filter.drop(['Unnamed: 0','index'], axis=1)\n",
        "df_filter.tail() #[-50:]"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Datum</th>\n",
              "      <th>UML</th>\n",
              "      <th>Wagen</th>\n",
              "      <th>Ab_ZT_PLAN</th>\n",
              "      <th>Linie</th>\n",
              "      <th>Haltestelle</th>\n",
              "      <th>Fahrplanlage_IST</th>\n",
              "      <th>v_PLAN</th>\n",
              "      <th>v_IST_S2S1</th>\n",
              "      <th>v_netto_S2S1</th>\n",
              "      <th>FFVP_GESCHWINDIGKEIT</th>\n",
              "      <th>v_IST</th>\n",
              "      <th>Ank_ZT_PLAN</th>\n",
              "      <th>S_Station</th>\n",
              "      <th>E_Station</th>\n",
              "      <th>NHaltestelle</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>date</th>\n",
              "      <th>Ab_ZT_ACTUAL</th>\n",
              "      <th>Ank_ZT_ACTUAL</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>Distance_m</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Distance_m_p</th>\n",
              "      <th>TagMean</th>\n",
              "      <th>TagRound</th>\n",
              "      <th>MESS_DATUM</th>\n",
              "      <th>R1</th>\n",
              "      <th>Precipitation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>673736</th>\n",
              "      <td>673736</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>77200.0</td>\n",
              "      <td>1612.0</td>\n",
              "      <td>2019-10-24 18:53:00</td>\n",
              "      <td>28.0</td>\n",
              "      <td>U Habichtstraße</td>\n",
              "      <td>14.7</td>\n",
              "      <td>19.8</td>\n",
              "      <td>4.7</td>\n",
              "      <td>3.8</td>\n",
              "      <td>0</td>\n",
              "      <td>4.1</td>\n",
              "      <td>2019-10-24 18:54:00</td>\n",
              "      <td>S Rübenkamp</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>Habichtstraße (Mitte)</td>\n",
              "      <td>U Habichtstraße|Habichtstraße (Mitte)</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>2019-10-24 19:07:42</td>\n",
              "      <td>2019-10-24 19:12:18</td>\n",
              "      <td>276.0</td>\n",
              "      <td>314.333333</td>\n",
              "      <td>60.0</td>\n",
              "      <td>330.000000</td>\n",
              "      <td>2019-10-24 18:53:30</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>2.019102e+09</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673737</th>\n",
              "      <td>673737</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>77200.0</td>\n",
              "      <td>1612.0</td>\n",
              "      <td>2019-10-24 18:54:00</td>\n",
              "      <td>28.0</td>\n",
              "      <td>Habichtstraße (Mitte)</td>\n",
              "      <td>18.3</td>\n",
              "      <td>16.1</td>\n",
              "      <td>7.4</td>\n",
              "      <td>6.9</td>\n",
              "      <td>0</td>\n",
              "      <td>6.7</td>\n",
              "      <td>2019-10-24 18:57:00</td>\n",
              "      <td>S Rübenkamp</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>U Alter Teichweg</td>\n",
              "      <td>Habichtstraße (Mitte)|U Alter Teichweg</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>2019-10-24 19:12:18</td>\n",
              "      <td>2019-10-24 19:19:42</td>\n",
              "      <td>444.0</td>\n",
              "      <td>826.333333</td>\n",
              "      <td>180.0</td>\n",
              "      <td>805.000000</td>\n",
              "      <td>2019-10-24 18:55:30</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>2.019102e+09</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673738</th>\n",
              "      <td>673738</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>77200.0</td>\n",
              "      <td>1612.0</td>\n",
              "      <td>2019-10-24 18:57:00</td>\n",
              "      <td>28.0</td>\n",
              "      <td>U Alter Teichweg</td>\n",
              "      <td>22.7</td>\n",
              "      <td>20.9</td>\n",
              "      <td>8.6</td>\n",
              "      <td>6.8</td>\n",
              "      <td>0</td>\n",
              "      <td>6.9</td>\n",
              "      <td>2019-10-24 18:59:00</td>\n",
              "      <td>S Rübenkamp</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>U Straßburger Straße</td>\n",
              "      <td>U Alter Teichweg|U Straßburger Straße</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>2019-10-24 19:19:42</td>\n",
              "      <td>2019-10-24 19:25:30</td>\n",
              "      <td>348.0</td>\n",
              "      <td>667.000000</td>\n",
              "      <td>120.0</td>\n",
              "      <td>696.666667</td>\n",
              "      <td>2019-10-24 18:58:00</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>2.019102e+09</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673739</th>\n",
              "      <td>673739</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>77200.0</td>\n",
              "      <td>1612.0</td>\n",
              "      <td>2019-10-24 18:59:00</td>\n",
              "      <td>28.0</td>\n",
              "      <td>U Straßburger Straße</td>\n",
              "      <td>26.5</td>\n",
              "      <td>18.1</td>\n",
              "      <td>-</td>\n",
              "      <td>-</td>\n",
              "      <td>19</td>\n",
              "      <td>11.9</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>S Rübenkamp</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>U Straßburger Straße|Wandsbeker Allee</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>2019-10-24 19:25:30</td>\n",
              "      <td>2019-10-24 19:27:00</td>\n",
              "      <td>90.0</td>\n",
              "      <td>297.500000</td>\n",
              "      <td>60.0</td>\n",
              "      <td>301.666667</td>\n",
              "      <td>2019-10-24 18:59:30</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>2.019102e+09</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673740</th>\n",
              "      <td>673740</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>77200.0</td>\n",
              "      <td>1612.0</td>\n",
              "      <td>2019-10-24 19:00:00</td>\n",
              "      <td>28.0</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>27.0</td>\n",
              "      <td>19.4</td>\n",
              "      <td>-</td>\n",
              "      <td>-</td>\n",
              "      <td>34</td>\n",
              "      <td>-</td>\n",
              "      <td>2019-10-24 12:47:00</td>\n",
              "      <td>S Rübenkamp</td>\n",
              "      <td>Wandsbeker Allee</td>\n",
              "      <td>Source</td>\n",
              "      <td>Wandsbeker Allee|Source</td>\n",
              "      <td>24.10.2019</td>\n",
              "      <td>2019-10-24 19:27:00</td>\n",
              "      <td>2019-10-24 12:47:42</td>\n",
              "      <td>-23958.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-22380.0</td>\n",
              "      <td>-120603.333333</td>\n",
              "      <td>2019-10-24 15:53:30</td>\n",
              "      <td>2019-10-24 16:00:00</td>\n",
              "      <td>2.019102e+09</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Unnamed: 0       Datum      UML  ...    MESS_DATUM   R1  Precipitation\n",
              "673736      673736  24.10.2019  77200.0  ...  2.019102e+09  0.0            0.0\n",
              "673737      673737  24.10.2019  77200.0  ...  2.019102e+09  0.0            0.0\n",
              "673738      673738  24.10.2019  77200.0  ...  2.019102e+09  0.0            0.0\n",
              "673739      673739  24.10.2019  77200.0  ...  2.019102e+09  0.0            0.0\n",
              "673740      673740  24.10.2019  77200.0  ...  2.019102e+09  0.0            0.0\n",
              "\n",
              "[5 rows x 30 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a_Zr5uID1RjB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c9321f6f-3ad5-4851-84cd-feab7d4a6b02"
      },
      "source": [
        "# Checking how many unique lines there are in the dataframe\n",
        "len(df_filter.Linie.unique())"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xeUBQWvQ3IXr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1496817e-33c7-4a4b-d38e-8603b0fafac4"
      },
      "source": [
        "df_filter.dtypes"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0                       int64\n",
              "Datum                           object\n",
              "UML                            float64\n",
              "Wagen                          float64\n",
              "Ab_ZT_PLAN              datetime64[ns]\n",
              "Linie                          float64\n",
              "Haltestelle                     object\n",
              "Fahrplanlage_IST               float64\n",
              "v_PLAN                         float64\n",
              "v_IST_S2S1                      object\n",
              "v_netto_S2S1                    object\n",
              "FFVP_GESCHWINDIGKEIT            object\n",
              "v_IST                           object\n",
              "Ank_ZT_PLAN             datetime64[ns]\n",
              "S_Station                       object\n",
              "E_Station                       object\n",
              "NHaltestelle                    object\n",
              "Node A to Node B                object\n",
              "date                            object\n",
              "Ab_ZT_ACTUAL                    object\n",
              "Ank_ZT_ACTUAL                   object\n",
              "Driving_time_s                 float64\n",
              "Distance_m                     float64\n",
              "Driving_time_s_p               float64\n",
              "Distance_m_p                   float64\n",
              "TagMean                 datetime64[ns]\n",
              "TagRound                datetime64[ns]\n",
              "MESS_DATUM                     float64\n",
              "R1                             float64\n",
              "Precipitation                  float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lOofsa6LKGLP"
      },
      "source": [
        "df_filter['date']= pd.to_datetime(df_filter.date, format='%d.%m.%Y', errors='ignore') #change date format\n",
        "#df_filter.head()"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WrZtVZcpP51t"
      },
      "source": [
        "df_filter = df_filter.sort_values( ['date', 'Unnamed: 0']).reset_index(drop = True) #\n",
        "#df_filter.tail() #[-50:]"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yoyTcCXl8YLv"
      },
      "source": [
        "# **Select only relevent features**\n",
        "\n",
        "Features are selected based on Chen et al.(2004) paper."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-lirRY6PJUCh"
      },
      "source": [
        "## Journey 101 ***U Wandsbek Markt to S Rübenkamp***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MtgyLexe7PBP"
      },
      "source": [
        "df_selected = df_filter.loc[df_filter['S_Station'] == 'U Wandsbek Markt'].reset_index()\n",
        "df_selected = df_selected.loc[df_selected['E_Station'] == 'S Rübenkamp'].reset_index()\n",
        "df_selected = df_selected[['Ab_ZT_PLAN', 'TagRound', 'UML', 'Linie', 'Node A to Node B', 'Precipitation', 'Driving_time_s_p', 'Driving_time_s']]\n",
        "#df_selected = df_selected.loc[df_selected['UML'] == 77082]\n",
        "df_selected = df_selected.loc[df_selected['Linie']  == 28].reset_index()\n",
        "df_selected = df_selected.loc[(df_selected['Driving_time_s']  <= 1000) & (df_selected['Driving_time_s']  >= 0)].reset_index()\n",
        "df_selected = df_selected.drop(['Linie', 'TagRound', 'index', 'UML', 'level_0'], axis=1)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AXwNmsMjVSo-"
      },
      "source": [
        "df_selected= df_selected.rename({'Ab_ZT_PLAN': 'Time'}, axis=1)"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lxbJ5cuY7f5E"
      },
      "source": [
        "#df_selected"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "civ6fXaM12bg"
      },
      "source": [
        "import math\n",
        "df_selected['dayofweek'] = df_selected['Time'].dt.dayofweek\n",
        "df_selected['hour'] = (df_selected['Time'].dt.hour+1)\n",
        "df_selected['day'] = df_selected['Time'].dt.day\n",
        "df_selected['month'] = df_selected['Time'].dt.month\n",
        "df_selected['timeofday'] = [0 for number in df_selected['Time']]\n",
        "#df_selected"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0SO7sFHdfVMK"
      },
      "source": [
        "Filter Holidays out"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QUBDG_P4fUqJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "7a9eeb4e-9843-4da4-948b-3ba592a6478b"
      },
      "source": [
        "#df_selected = df_selected[~df_selected['day'].isin([19,22])].reset_index() # for April dataset\n",
        "df_selected = df_selected.loc[~(((df_selected['day'] == 1) & (df_selected['month'] ==  1)) # for the whole year dataset\n",
        "                  |((df_selected['day'] == 19) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 21) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 22) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 1) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 30) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 10) & (df_selected['month'] == 6))\n",
        "                  |((df_selected['day'] == 3) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 31) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 25) & (df_selected['month'] == 12))\n",
        "                  |((df_selected['day'] == 26) & (df_selected['month'] == 12))\n",
        "                  ),:].reset_index()\n",
        "df_selected.tail() #[:50]"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>hour</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>133269</th>\n",
              "      <td>136831</td>\n",
              "      <td>2019-12-23 08:58:00</td>\n",
              "      <td>Habichtsplatz|Neue Wöhr</td>\n",
              "      <td>1.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>144.0</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133270</th>\n",
              "      <td>136832</td>\n",
              "      <td>2019-12-23 09:01:00</td>\n",
              "      <td>Neue Wöhr|Hartzloh</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133271</th>\n",
              "      <td>136833</td>\n",
              "      <td>2019-12-23 09:02:00</td>\n",
              "      <td>Hartzloh|AK Barmbek</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133272</th>\n",
              "      <td>136834</td>\n",
              "      <td>2019-12-23 09:03:00</td>\n",
              "      <td>AK Barmbek|Hebebrandstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133273</th>\n",
              "      <td>136835</td>\n",
              "      <td>2019-12-23 09:05:00</td>\n",
              "      <td>Hebebrandstraße|S Rübenkamp</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         index                Time  ... month  timeofday\n",
              "133269  136831 2019-12-23 08:58:00  ...    12          0\n",
              "133270  136832 2019-12-23 09:01:00  ...    12          0\n",
              "133271  136833 2019-12-23 09:02:00  ...    12          0\n",
              "133272  136834 2019-12-23 09:03:00  ...    12          0\n",
              "133273  136835 2019-12-23 09:05:00  ...    12          0\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RuRIXdj-elXO"
      },
      "source": [
        "Find high driving time period on day"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BlaJdgNgekZH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "d6d33297-abc7-40b5-ed9c-d5688c53ee3d"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(df_selected['hour'], df_selected['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('hour', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time on days by hour', fontsize=28)\n",
        "\n",
        "plt.tight_layout()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lFeFyNjbiETv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9493a8e2-38f1-43cb-c271-34febf7f2ad6"
      },
      "source": [
        "# manual clustering the hour\n",
        "for i in range(len(df_selected)):\n",
        "  #print('1')\n",
        "  if df_selected['hour'][i]<9:\n",
        "    df_selected['timeofday'][i] = 0\n",
        "  elif df_selected['hour'][i]<11:\n",
        "    df_selected['timeofday'][i] = 1\n",
        "  elif df_selected['hour'][i] < 16:\n",
        "    df_selected['timeofday'][i] = 2\n",
        "  elif df_selected['hour'][i] <20:\n",
        "    df_selected['timeofday'][i] = 3\n",
        "  else:\n",
        "    df_selected['timeofday'][i] = 4\n",
        "\n",
        "#df_selected\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # This is added back by InteractiveShellApp.init_path()\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  del sys.path[0]\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hJW2L1HDm27f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "a0106be3-282c-4634-aa07-754d309f8120"
      },
      "source": [
        "df_selected = df_selected.drop(['index','day','hour'], axis=1)\n",
        "df_selected"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-02 09:47:00</td>\n",
              "      <td>U Wandsbek Markt|Wandsbeker Allee</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>204.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-01-02 09:50:00</td>\n",
              "      <td>Wandsbeker Allee|U Straßburger Straße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>108.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-01-02 09:52:00</td>\n",
              "      <td>U Straßburger Straße|U Alter Teichweg</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-02 09:54:00</td>\n",
              "      <td>U Alter Teichweg|Habichtstraße (Mitte)</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>168.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-01-02 09:57:00</td>\n",
              "      <td>Habichtstraße (Mitte)|U Habichtstraße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133269</th>\n",
              "      <td>2019-12-23 08:58:00</td>\n",
              "      <td>Habichtsplatz|Neue Wöhr</td>\n",
              "      <td>1.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>144.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133270</th>\n",
              "      <td>2019-12-23 09:01:00</td>\n",
              "      <td>Neue Wöhr|Hartzloh</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133271</th>\n",
              "      <td>2019-12-23 09:02:00</td>\n",
              "      <td>Hartzloh|AK Barmbek</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133272</th>\n",
              "      <td>2019-12-23 09:03:00</td>\n",
              "      <td>AK Barmbek|Hebebrandstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133273</th>\n",
              "      <td>2019-12-23 09:05:00</td>\n",
              "      <td>Hebebrandstraße|S Rübenkamp</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>133274 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Time  ... timeofday\n",
              "0      2019-01-02 09:47:00  ...         1\n",
              "1      2019-01-02 09:50:00  ...         1\n",
              "2      2019-01-02 09:52:00  ...         1\n",
              "3      2019-01-02 09:54:00  ...         1\n",
              "4      2019-01-02 09:57:00  ...         1\n",
              "...                    ...  ...       ...\n",
              "133269 2019-12-23 08:58:00  ...         1\n",
              "133270 2019-12-23 09:01:00  ...         1\n",
              "133271 2019-12-23 09:02:00  ...         1\n",
              "133272 2019-12-23 09:03:00  ...         1\n",
              "133273 2019-12-23 09:05:00  ...         1\n",
              "\n",
              "[133274 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M8mIi2WO4l9s",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c1c9f57f-162f-48ac-dab4-1aacf591a151"
      },
      "source": [
        "len(df_selected['Node A to Node B'].unique())"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "29"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lC6JFW5SD6_R",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "edc8444f-b979-41ed-a5d8-251cbea7fe4f"
      },
      "source": [
        "df_selected.describe()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>133274.000000</td>\n",
              "      <td>133274.000000</td>\n",
              "      <td>133274.000000</td>\n",
              "      <td>133274.000000</td>\n",
              "      <td>133274.000000</td>\n",
              "      <td>133274.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-0.260103</td>\n",
              "      <td>100.369014</td>\n",
              "      <td>107.076729</td>\n",
              "      <td>3.573608</td>\n",
              "      <td>6.398165</td>\n",
              "      <td>2.623332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>16.747740</td>\n",
              "      <td>57.641203</td>\n",
              "      <td>90.010200</td>\n",
              "      <td>1.997125</td>\n",
              "      <td>3.273029</td>\n",
              "      <td>1.237864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-499.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>54.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>126.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>3480.000000</td>\n",
              "      <td>996.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Precipitation  Driving_time_s_p  ...          month      timeofday\n",
              "count  133274.000000     133274.000000  ...  133274.000000  133274.000000\n",
              "mean       -0.260103        100.369014  ...       6.398165       2.623332\n",
              "std        16.747740         57.641203  ...       3.273029       1.237864\n",
              "min      -499.000000         60.000000  ...       1.000000       0.000000\n",
              "25%         0.000000         60.000000  ...       4.000000       2.000000\n",
              "50%         0.000000        120.000000  ...       6.000000       3.000000\n",
              "75%         1.000000        120.000000  ...       9.000000       4.000000\n",
              "max         1.000000       3480.000000  ...      12.000000       4.000000\n",
              "\n",
              "[8 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lvpzPceR_L3R",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "0f256fb2-daa3-4de6-df8a-2691d41b3e3d"
      },
      "source": [
        "plt.hist(df_selected['Driving_time_s'])\n",
        "plt.show()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zb0gZ4Q8RVD3"
      },
      "source": [
        "data = df_selected.copy()"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h6HvVD1zSEuW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "efe0958e-bd15-4cba-a094-717545b7b2c7"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(data['Time'], data['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('Datetime [-]', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time of line 28 U Wandsbek Markt to S Rübenkamp', fontsize=28)\n",
        "\n",
        "plt.tight_layout()\n",
        "\n",
        "#plt.savefig('figures/available data.png', dpi=1200)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IWPMusLcXS-S"
      },
      "source": [
        "From this plot it is clear that the driving time is really fluctuate. The highest one is almost 4000 second.\n",
        "There are periods of missing data visible on every weekend."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o4MOq833Ypvb"
      },
      "source": [
        "**Add two new columns for accumulate values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5PGekd68V94Z"
      },
      "source": [
        "data.loc[data.Precipitation == -499 ]=0\n",
        "data = data.loc[data['Node A to Node B'].isin(['U Wandsbek Markt|Wandsbeker Allee',\n",
        "       'Wandsbeker Allee|U Straßburger Straße',\n",
        "       'U Straßburger Straße|U Alter Teichweg',\n",
        "       'U Alter Teichweg|Habichtstraße (Mitte)',\n",
        "       'Habichtstraße (Mitte)|U Habichtstraße',\n",
        "       'U Habichtstraße|Habichtsplatz', 'Habichtsplatz|Neue Wöhr',\n",
        "       'Neue Wöhr|Hartzloh', 'Hartzloh|AK Barmbek',\n",
        "       'AK Barmbek|Hebebrandstraße', 'Hebebrandstraße|S Rübenkamp'])]"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JbqHWKgGYPdI"
      },
      "source": [
        "data =data.reset_index(drop=True)"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EMko_PxsVg9b",
        "outputId": "cfffb074-b89b-4a47-e1a1-7eef19015398"
      },
      "source": [
        "route_unique = (data['Node A to Node B'].unique())\n",
        "route_unique"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['U Wandsbek Markt|Wandsbeker Allee',\n",
              "       'Wandsbeker Allee|U Straßburger Straße',\n",
              "       'U Straßburger Straße|U Alter Teichweg',\n",
              "       'U Alter Teichweg|Habichtstraße (Mitte)',\n",
              "       'Habichtstraße (Mitte)|U Habichtstraße',\n",
              "       'U Habichtstraße|Habichtsplatz', 'Habichtsplatz|Neue Wöhr',\n",
              "       'Neue Wöhr|Hartzloh', 'Hartzloh|AK Barmbek',\n",
              "       'AK Barmbek|Hebebrandstraße', 'Hebebrandstraße|S Rübenkamp'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "id": "Y8DqGxFWUaxz",
        "outputId": "6d57535e-f968-4c24-ecb9-bff7aeaa0615"
      },
      "source": [
        "#act_p = []\n",
        "data['Actual_trip_cum'] = 0\n",
        "data['Planned_trip_cum'] = 0\n",
        "a = 0\n",
        "b = 0\n",
        "\n",
        "for i in range(len(data)):\n",
        "  #print(i)\n",
        "  if data['Node A to Node B'][i] == route_unique[0]: #the first path\n",
        "    a = data['Driving_time_s'][i]\n",
        "    data['Actual_trip_cum'][i] = a\n",
        "    b = data['Driving_time_s_p'][i]\n",
        "    data['Planned_trip_cum'][i] = b\n",
        "  else:\n",
        "    a += data['Driving_time_s'][i] \n",
        "    data['Actual_trip_cum'][i] = a\n",
        "    b += data['Driving_time_s_p'][i]\n",
        "    data['Planned_trip_cum'][i] = b\n",
        "data.tail() #[:50]"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # This is added back by InteractiveShellApp.init_path()\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  del sys.path[0]\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  app.launch_new_instance()\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:18: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "      <th>Actual_trip_cum</th>\n",
              "      <th>Planned_trip_cum</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>132959</th>\n",
              "      <td>2019-12-23 08:58:00</td>\n",
              "      <td>Habichtsplatz|Neue Wöhr</td>\n",
              "      <td>1.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>144.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>864</td>\n",
              "      <td>900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132960</th>\n",
              "      <td>2019-12-23 09:01:00</td>\n",
              "      <td>Neue Wöhr|Hartzloh</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>930</td>\n",
              "      <td>960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132961</th>\n",
              "      <td>2019-12-23 09:02:00</td>\n",
              "      <td>Hartzloh|AK Barmbek</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>990</td>\n",
              "      <td>1020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132962</th>\n",
              "      <td>2019-12-23 09:03:00</td>\n",
              "      <td>AK Barmbek|Hebebrandstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>1122</td>\n",
              "      <td>1140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132963</th>\n",
              "      <td>2019-12-23 09:05:00</td>\n",
              "      <td>Hebebrandstraße|S Rübenkamp</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>1182</td>\n",
              "      <td>1260</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Time  ... Planned_trip_cum\n",
              "132959  2019-12-23 08:58:00  ...              900\n",
              "132960  2019-12-23 09:01:00  ...              960\n",
              "132961  2019-12-23 09:02:00  ...             1020\n",
              "132962  2019-12-23 09:03:00  ...             1140\n",
              "132963  2019-12-23 09:05:00  ...             1260\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V0mhtnTHPl2Q"
      },
      "source": [
        "#data = data.loc[data.month<3]"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EJHgQMKOUPMV",
        "cellView": "code"
      },
      "source": [
        "#data.to_csv('ist_0420_data_processed.csv')\n",
        "#!cp ist_0420_data_processed.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\"\n",
        "data.to_csv('ist_01_12_19_data_processed.csv')\n",
        "!cp ist_01_12_19_data_processed.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\""
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qrc_yowFMoOW"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "Same procedure implement on other journeys.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s2ooKJjgK_MN"
      },
      "source": [
        "## Journey 102 ***S Rübenkamp to U Wandsbek Markt***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "89lypCPNYuxK"
      },
      "source": [
        "df_selected = df_filter.loc[df_filter['S_Station'] == 'S Rübenkamp'].reset_index()\n",
        "df_selected = df_selected.loc[df_selected['E_Station'] == 'U Wandsbek Markt'].reset_index()\n",
        "df_selected = df_selected[['Ab_ZT_PLAN', 'TagRound', 'UML', 'Linie', 'Node A to Node B', 'Precipitation', 'Driving_time_s_p', 'Driving_time_s']]\n",
        "#df_selected = df_selected.loc[df_selected['UML'] == 77082]\n",
        "df_selected = df_selected.loc[df_selected['Linie']  == 28].reset_index()\n",
        "df_selected = df_selected.loc[(df_selected['Driving_time_s']  <= 1000) & (df_selected['Driving_time_s']  >= 0)].reset_index()\n",
        "df_selected = df_selected.drop(['Linie', 'TagRound', 'index', 'UML', 'level_0'], axis=1)\n",
        "df_selected= df_selected.rename({'Ab_ZT_PLAN': 'Time'}, axis=1)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9uQI3rN2M0KP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "11333a21-eaad-4ccb-8fd0-98323ffe9bce"
      },
      "source": [
        "import math\n",
        "df_selected['dayofweek'] = df_selected['Time'].dt.dayofweek\n",
        "df_selected['hour'] = (df_selected['Time'].dt.hour+1)\n",
        "df_selected['day'] = df_selected['Time'].dt.day\n",
        "df_selected['month'] = df_selected['Time'].dt.month\n",
        "df_selected['timeofday'] = [0 for number in df_selected['Time']]\n",
        "df_selected"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>hour</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-01 15:05:00</td>\n",
              "      <td>S Rübenkamp|AK Barmbek</td>\n",
              "      <td>1.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>198.0</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-01-01 15:08:00</td>\n",
              "      <td>AK Barmbek|Hartzloh</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-01-01 15:10:00</td>\n",
              "      <td>Hartzloh|Habichtsplatz</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-01 15:12:00</td>\n",
              "      <td>Habichtsplatz|U Habichtstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-01-01 15:13:00</td>\n",
              "      <td>U Habichtstraße|Habichtstraße (Mitte)</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>108.0</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67672</th>\n",
              "      <td>2019-12-14 18:21:00</td>\n",
              "      <td>U Habichtstraße|Habichtstraße (Mitte)</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67673</th>\n",
              "      <td>2019-12-14 18:23:00</td>\n",
              "      <td>Habichtstraße (Mitte)|U Alter Teichweg</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67674</th>\n",
              "      <td>2019-12-14 18:26:00</td>\n",
              "      <td>U Alter Teichweg|U Straßburger Straße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>408.0</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67675</th>\n",
              "      <td>2019-12-14 18:28:00</td>\n",
              "      <td>U Straßburger Straße|Wandsbeker Allee</td>\n",
              "      <td>0.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67676</th>\n",
              "      <td>2019-12-14 18:29:00</td>\n",
              "      <td>Wandsbeker Allee|U Wandsbek Markt</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>67677 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Time  ... timeofday\n",
              "0     2019-01-01 15:05:00  ...         0\n",
              "1     2019-01-01 15:08:00  ...         0\n",
              "2     2019-01-01 15:10:00  ...         0\n",
              "3     2019-01-01 15:12:00  ...         0\n",
              "4     2019-01-01 15:13:00  ...         0\n",
              "...                   ...  ...       ...\n",
              "67672 2019-12-14 18:21:00  ...         0\n",
              "67673 2019-12-14 18:23:00  ...         0\n",
              "67674 2019-12-14 18:26:00  ...         0\n",
              "67675 2019-12-14 18:28:00  ...         0\n",
              "67676 2019-12-14 18:29:00  ...         0\n",
              "\n",
              "[67677 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ceXeHHd7NCHq"
      },
      "source": [
        "Filter Holidays out, 19 and 22"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zmF2Nc2INAUr"
      },
      "source": [
        "#df_selected = df_selected[~df_selected['day'].isin([19,22])].reset_index()\n",
        "df_selected = df_selected.loc[~(((df_selected['day'] == 1) & (df_selected['month'] ==  1))\n",
        "                  |((df_selected['day'] == 19) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 21) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 22) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 1) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 30) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 10) & (df_selected['month'] == 6))\n",
        "                  |((df_selected['day'] == 3) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 31) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 25) & (df_selected['month'] == 12))\n",
        "                  |((df_selected['day'] == 26) & (df_selected['month'] == 12))\n",
        "                  ),:].reset_index()\n",
        "#df_selected.tail() #[:50]"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wKJhXqUqNcBO"
      },
      "source": [
        "Find driving time pattern to define peak hours"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nlvgglb-NRA5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "ffe06d99-0629-445a-9678-4bc532b3e8ba"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(df_selected['hour'], df_selected['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('hour', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time on days by hour', fontsize=28)\n",
        "\n",
        "plt.tight_layout()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kn0LzqsXNrDB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "45373a64-f201-458b-8f3a-ee46435ed404"
      },
      "source": [
        "for i in range(len(df_selected)):\n",
        "  #print('1')\n",
        "  if df_selected['hour'][i]<10:\n",
        "    df_selected['timeofday'][i] = 0\n",
        "  elif df_selected['hour'][i]<16:\n",
        "    df_selected['timeofday'][i] = 1\n",
        "  elif df_selected['hour'][i] < 18:\n",
        "    df_selected['timeofday'][i] = 2\n",
        "  elif df_selected['hour'][i] <21:\n",
        "    df_selected['timeofday'][i] = 3\n",
        "  else:\n",
        "    df_selected['timeofday'][i] = 4\n",
        "\n",
        "#df_selected"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # Remove the CWD from sys.path while we load stuff.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wjo5G7fcRXgA"
      },
      "source": [
        "df_selected = df_selected.drop(['index','day','hour'], axis=1)\n",
        "#df_selected"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "imNuAxUzRYUw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bde6d18e-b39f-4fcf-9ed7-70f75f17ddca"
      },
      "source": [
        "len(df_selected['Node A to Node B'].unique())"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "15"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "96WPSZ5BAT8L",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "ca0dd46d-d9cb-4de7-cd88-14ff2b867833"
      },
      "source": [
        "df_selected.describe()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>65563.000000</td>\n",
              "      <td>65563.000000</td>\n",
              "      <td>65563.000000</td>\n",
              "      <td>65563.000000</td>\n",
              "      <td>65563.000000</td>\n",
              "      <td>65563.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-0.624758</td>\n",
              "      <td>115.597212</td>\n",
              "      <td>120.215609</td>\n",
              "      <td>3.677226</td>\n",
              "      <td>4.881046</td>\n",
              "      <td>1.99126</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>21.256677</td>\n",
              "      <td>58.405635</td>\n",
              "      <td>67.468726</td>\n",
              "      <td>1.980093</td>\n",
              "      <td>2.503362</td>\n",
              "      <td>1.47269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-499.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>108.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>1.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>156.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>4.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>480.000000</td>\n",
              "      <td>996.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>4.00000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Precipitation  Driving_time_s_p  ...         month    timeofday\n",
              "count   65563.000000      65563.000000  ...  65563.000000  65563.00000\n",
              "mean       -0.624758        115.597212  ...      4.881046      1.99126\n",
              "std        21.256677         58.405635  ...      2.503362      1.47269\n",
              "min      -499.000000         60.000000  ...      1.000000      0.00000\n",
              "25%         0.000000         60.000000  ...      3.000000      1.00000\n",
              "50%         0.000000        120.000000  ...      5.000000      1.00000\n",
              "75%         1.000000        120.000000  ...      7.000000      4.00000\n",
              "max         1.000000        480.000000  ...     12.000000      4.00000\n",
              "\n",
              "[8 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MSU18pFlAizp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "a7b57e91-e51d-4ad4-e172-5949b7a77522"
      },
      "source": [
        "plt.hist(df_selected['Driving_time_s'])\n",
        "plt.show()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BQ5zVA5dRcGM"
      },
      "source": [
        "data102 = df_selected.copy()"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4VO_j43wRmZR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "45e6b294-df04-4015-d528-ba43f760e673"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(data102['Time'], data102['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('Datetime [-]', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time of line 28 S Rübenkamp to U Wandsbek Markt', fontsize=28)\n",
        "\n",
        "plt.tight_layout()\n",
        "\n",
        "#plt.savefig('figures/available data.png', dpi=1200)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5nov1rDNiEan"
      },
      "source": [
        "**Add two new columns for accumulate values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "btcZ6yeDg8IO"
      },
      "source": [
        "data102.loc[data102.Precipitation == -499 ]=0\n",
        "data102 = data102.loc[data102['Node A to Node B'].isin(['U Straßburger Straße|Wandsbeker Allee',\n",
        "'AK Barmbek|Hartzloh',\n",
        "'U Habichtstraße|Habichtstraße (Mitte)',\n",
        "'Habichtsplatz|U Habichtstraße',\n",
        "'U Alter Teichweg|U Straßburger Straße',\n",
        "'Wandsbeker Allee|U Wandsbek Markt',\n",
        "'Hartzloh|Habichtsplatz',\n",
        "'S Rübenkamp|AK Barmbek',\n",
        "'Habichtstraße (Mitte)|U Alter Teichweg'])]"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3XixDnSOhc-P"
      },
      "source": [
        "data102 =data102.reset_index(drop=True)"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TNxnTZ1ChfHL",
        "outputId": "cd088703-be5e-466f-c7c6-322ecefe1126"
      },
      "source": [
        "route_unique = (data102['Node A to Node B'].unique())\n",
        "route_unique"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['S Rübenkamp|AK Barmbek', 'AK Barmbek|Hartzloh',\n",
              "       'Hartzloh|Habichtsplatz', 'Habichtsplatz|U Habichtstraße',\n",
              "       'U Habichtstraße|Habichtstraße (Mitte)',\n",
              "       'Habichtstraße (Mitte)|U Alter Teichweg',\n",
              "       'U Alter Teichweg|U Straßburger Straße',\n",
              "       'U Straßburger Straße|Wandsbeker Allee',\n",
              "       'Wandsbeker Allee|U Wandsbek Markt'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "id": "gLNUHaOQhkUY",
        "outputId": "fe8e883c-4a52-493b-eb2e-88b4037b86e7"
      },
      "source": [
        "#act_p = []\n",
        "data102['Actual_trip_cum'] = 0\n",
        "data102['Planned_trip_cum'] = 0\n",
        "a = 0\n",
        "b = 0\n",
        "\n",
        "for i in range(len(data102)):\n",
        "  #print(i)\n",
        "  if data102['Node A to Node B'][i] == route_unique[0]: #the first path\n",
        "    a = data102['Driving_time_s'][i]\n",
        "    data102['Actual_trip_cum'][i] = a\n",
        "    b = data102['Driving_time_s_p'][i]\n",
        "    data102['Planned_trip_cum'][i] = b\n",
        "  else:\n",
        "    a += data102['Driving_time_s'][i] \n",
        "    data102['Actual_trip_cum'][i] = a\n",
        "    b += data102['Driving_time_s_p'][i]\n",
        "    data102['Planned_trip_cum'][i] = b\n",
        "data102.tail() #[:50]"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # This is added back by InteractiveShellApp.init_path()\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  del sys.path[0]\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  app.launch_new_instance()\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:18: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "      <th>Actual_trip_cum</th>\n",
              "      <th>Planned_trip_cum</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>62055</th>\n",
              "      <td>2019-12-14 18:21:00</td>\n",
              "      <td>U Habichtstraße|Habichtstraße (Mitte)</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>462</td>\n",
              "      <td>480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62056</th>\n",
              "      <td>2019-12-14 18:23:00</td>\n",
              "      <td>Habichtstraße (Mitte)|U Alter Teichweg</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>594</td>\n",
              "      <td>660</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62057</th>\n",
              "      <td>2019-12-14 18:26:00</td>\n",
              "      <td>U Alter Teichweg|U Straßburger Straße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>408.0</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>1002</td>\n",
              "      <td>780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62058</th>\n",
              "      <td>2019-12-14 18:28:00</td>\n",
              "      <td>U Straßburger Straße|Wandsbeker Allee</td>\n",
              "      <td>0.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>1104</td>\n",
              "      <td>840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62059</th>\n",
              "      <td>2019-12-14 18:29:00</td>\n",
              "      <td>Wandsbeker Allee|U Wandsbek Markt</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>1200</td>\n",
              "      <td>1020</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Time  ... Planned_trip_cum\n",
              "62055  2019-12-14 18:21:00  ...              480\n",
              "62056  2019-12-14 18:23:00  ...              660\n",
              "62057  2019-12-14 18:26:00  ...              780\n",
              "62058  2019-12-14 18:28:00  ...              840\n",
              "62059  2019-12-14 18:29:00  ...             1020\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EXoJdrX_SLpp"
      },
      "source": [
        "Save to csv"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "okqXp-TxR8H-"
      },
      "source": [
        "#data102.to_csv('ist_0420_data_processed102.csv')\n",
        "#!cp ist_0420_data_processed102.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\"\n",
        "data102.to_csv('ist_01_12_19_data_processed102.csv')\n",
        "!cp ist_01_12_19_data_processed102.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\""
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kmYv77UJSQwT"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gtQ8OwBvUBk8"
      },
      "source": [
        "## Journey 201 ***U Wandsbek Markt to Lufthansa-Basis (Haupteingang)***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "twKfrvSaSR-b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "8db46832-89d6-4a3a-cc29-294b00174b92"
      },
      "source": [
        "df_selected = df_filter.loc[df_filter['S_Station'] == 'U Wandsbek Markt'].reset_index()\n",
        "df_selected = df_selected.loc[df_selected['E_Station'] == 'Lufthansa-Basis (Haupteingang)'].reset_index()\n",
        "df_selected = df_selected[['Ab_ZT_PLAN', 'TagRound', 'UML', 'Linie', 'Node A to Node B', 'Precipitation', 'Driving_time_s_p', 'Driving_time_s']]\n",
        "#df_selected = df_selected.loc[df_selected['UML'] == 77082]\n",
        "df_selected = df_selected.loc[df_selected['Linie']  == 28].reset_index()\n",
        "df_selected = df_selected.loc[(df_selected['Driving_time_s']  <= 1000) & (df_selected['Driving_time_s']  >= 0)].reset_index()\n",
        "df_selected = df_selected.drop(['Linie', 'TagRound', 'index', 'UML', 'level_0'], axis=1)\n",
        "df_selected= df_selected.rename({'Ab_ZT_PLAN': 'Time'}, axis=1)\n",
        "df_selected"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>Node A to Node B</th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-01-02 10:57:00</td>\n",
              "      <td>U Wandsbek Markt|Wandsbeker Allee</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>186.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-01-02 11:00:00</td>\n",
              "      <td>Wandsbeker Allee|U Straßburger Straße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>84.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-01-02 11:02:00</td>\n",
              "      <td>U Straßburger Straße|U Alter Teichweg</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-01-02 11:04:00</td>\n",
              "      <td>U Alter Teichweg|Habichtstraße (Mitte)</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>162.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-01-02 11:07:00</td>\n",
              "      <td>Habichtstraße (Mitte)|U Habichtstraße</td>\n",
              "      <td>0.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162447</th>\n",
              "      <td>2019-12-23 07:33:00</td>\n",
              "      <td>Hindenburgstraße|Brabandstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>90.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162448</th>\n",
              "      <td>2019-12-23 07:35:00</td>\n",
              "      <td>Brabandstraße|Moltrechtweg</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>66.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162449</th>\n",
              "      <td>2019-12-23 07:36:00</td>\n",
              "      <td>Moltrechtweg|Alsterkrugchaussee (Mitte)</td>\n",
              "      <td>1.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162450</th>\n",
              "      <td>2019-12-23 07:38:00</td>\n",
              "      <td>Alsterkrugchaussee (Mitte)|Obenhauptstraße</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>72.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162451</th>\n",
              "      <td>2019-12-23 07:39:00</td>\n",
              "      <td>Obenhauptstraße|Lufthansa-Basis (Haupteingang)</td>\n",
              "      <td>1.0</td>\n",
              "      <td>240.0</td>\n",
              "      <td>144.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>162452 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Time  ... Driving_time_s\n",
              "0      2019-01-02 10:57:00  ...          186.0\n",
              "1      2019-01-02 11:00:00  ...           84.0\n",
              "2      2019-01-02 11:02:00  ...          102.0\n",
              "3      2019-01-02 11:04:00  ...          162.0\n",
              "4      2019-01-02 11:07:00  ...           36.0\n",
              "...                    ...  ...            ...\n",
              "162447 2019-12-23 07:33:00  ...           90.0\n",
              "162448 2019-12-23 07:35:00  ...           66.0\n",
              "162449 2019-12-23 07:36:00  ...          102.0\n",
              "162450 2019-12-23 07:38:00  ...           72.0\n",
              "162451 2019-12-23 07:39:00  ...          144.0\n",
              "\n",
              "[162452 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HJolQKnsSuk7"
      },
      "source": [
        "import math\n",
        "df_selected['dayofweek'] = df_selected['Time'].dt.dayofweek\n",
        "df_selected['hour'] = (df_selected['Time'].dt.hour+1)\n",
        "df_selected['day'] = df_selected['Time'].dt.day\n",
        "df_selected['month'] = df_selected['Time'].dt.month\n",
        "df_selected['timeofday'] = [0 for number in df_selected['Time']]\n",
        "#df_selected"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y2nGA67MVTG3"
      },
      "source": [
        "Filter Holidays, 19 and 22"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-AXUiq5LSwhG"
      },
      "source": [
        "#df_selected = df_selected[~df_selected['day'].isin([19,22])].reset_index()\n",
        "df_selected = df_selected.loc[~(((df_selected['day'] == 1) & (df_selected['month'] ==  1))\n",
        "                  |((df_selected['day'] == 19) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 21) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 22) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 1) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 30) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 10) & (df_selected['month'] == 6))\n",
        "                  |((df_selected['day'] == 3) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 31) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 25) & (df_selected['month'] == 12))\n",
        "                  |((df_selected['day'] == 26) & (df_selected['month'] == 12))\n",
        "                  ),:].reset_index()\n",
        "#df_selected[:50]"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0T-NI6RLVeT2"
      },
      "source": [
        "Find driving time pattern of peak hours"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "owUzJBUwVYF1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "7f9a99c5-9956-44ca-8c5f-eb66fd34e053"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(df_selected['hour'], df_selected['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('hour', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time on days by hour', fontsize=28)\n",
        "\n",
        "plt.tight_layout()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lEfRpLOlVbvk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6d310b93-489d-4e39-c786-f030f5123300"
      },
      "source": [
        "for i in range(len(df_selected)):\n",
        "  #print('1')\n",
        "  if df_selected['hour'][i]<7:\n",
        "    df_selected['timeofday'][i] = 0\n",
        "  elif df_selected['hour'][i]<11:\n",
        "    df_selected['timeofday'][i] = 1\n",
        "  elif df_selected['hour'][i] < 15:\n",
        "    df_selected['timeofday'][i] = 2\n",
        "  elif df_selected['hour'][i] <19:\n",
        "    df_selected['timeofday'][i] = 3\n",
        "  elif df_selected['hour'][i] <22:\n",
        "    df_selected['timeofday'][i] = 4\n",
        "  else:\n",
        "    df_selected['timeofday'][i] = 5\n",
        "\n",
        "#df_selected\n"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # Remove the CWD from sys.path while we load stuff.\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RrIZDYm-WC-q"
      },
      "source": [
        "df_selected = df_selected.drop(['index','day','hour'], axis=1)\n",
        "#df_selected"
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EbeuDdHvWDdk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "45aefc10-8aa2-456f-b4cf-5b45c5d09b5e"
      },
      "source": [
        "len(df_selected['Node A to Node B'].unique())"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "58"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YKWUaj5OA5zY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "2716ca72-cc44-4de9-c6e5-9c1ffa588d55"
      },
      "source": [
        "df_selected.describe()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Precipitation</th>\n",
              "      <th>Driving_time_s_p</th>\n",
              "      <th>Driving_time_s</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>month</th>\n",
              "      <th>timeofday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>162452.000000</td>\n",
              "      <td>162452.000000</td>\n",
              "      <td>162452.000000</td>\n",
              "      <td>162452.000000</td>\n",
              "      <td>162452.000000</td>\n",
              "      <td>162452.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-0.113486</td>\n",
              "      <td>101.865413</td>\n",
              "      <td>113.753503</td>\n",
              "      <td>2.006150</td>\n",
              "      <td>6.581107</td>\n",
              "      <td>2.134384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>14.179904</td>\n",
              "      <td>47.026426</td>\n",
              "      <td>94.500650</td>\n",
              "      <td>1.428886</td>\n",
              "      <td>3.140865</td>\n",
              "      <td>1.226916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-499.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>84.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>132.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1500.000000</td>\n",
              "      <td>996.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Precipitation  Driving_time_s_p  ...          month      timeofday\n",
              "count  162452.000000     162452.000000  ...  162452.000000  162452.000000\n",
              "mean       -0.113486        101.865413  ...       6.581107       2.134384\n",
              "std        14.179904         47.026426  ...       3.140865       1.226916\n",
              "min      -499.000000         60.000000  ...       1.000000       0.000000\n",
              "25%         0.000000         60.000000  ...       4.000000       1.000000\n",
              "50%         0.000000        120.000000  ...       7.000000       2.000000\n",
              "75%         1.000000        120.000000  ...       9.000000       3.000000\n",
              "max         1.000000       1500.000000  ...      12.000000       5.000000\n",
              "\n",
              "[8 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dVS0dApkA4jr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "5a5e646b-dbdb-4a9f-af9d-7bf1cc0c0fd6"
      },
      "source": [
        "plt.hist(df_selected['Driving_time_s'])\n",
        "plt.show()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B_XGYMHuWFrn"
      },
      "source": [
        "data201 = df_selected.copy()"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Flq5U-tKWJSe"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(data201['Time'], data201['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('Datetime [-]', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time of line 28 U Wandsbek Markt to Lufthansa-Basis (Haupteingang)', fontsize=28)\n",
        "\n",
        "plt.tight_layout()\n",
        "\n",
        "#plt.savefig('figures/available data.png', dpi=1200)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Oq_QZ7BliGDp"
      },
      "source": [
        "**Add two new columns for accumulate values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sVKQQxd6h5UQ"
      },
      "source": [
        "data201.loc[data201.Precipitation == -499 ]=0\n",
        "data201 = data201.loc[data201['Node A to Node B'].isin(['Kapstadtring|Manilabrücke',\n",
        "'U Alsterdorf|Hindenburgstraße',\n",
        "'Habichtstraße (Mitte)|U Habichtstraße',\n",
        "'Neue Wöhr|Hartzloh',\n",
        "'Hartzloh|AK Barmbek',\n",
        "'Brabandstraße|Moltrechtweg',\n",
        "'Alsterkrugchaussee (Mitte)|Obenhauptstraße',\n",
        "'Manilabrücke|Sydneystraße',\n",
        "'Hebebrandstraße|S Rübenkamp',\n",
        "'U Habichtstraße|Habichtsplatz',\n",
        "'Moltrechtweg|Alsterkrugchaussee (Mitte)',\n",
        "'Hindenburgstraße|Brabandstraße',\n",
        "'S Rübenkamp|Kapstadtring',\n",
        "'Wandsbeker Allee|U Straßburger Straße',\n",
        "'Sydneystraße|U Alsterdorf',\n",
        "'Habichtsplatz|Neue Wöhr',\n",
        "'AK Barmbek|Hebebrandstraße',\n",
        "'U Straßburger Straße|U Alter Teichweg',\n",
        "'Obenhauptstraße|Lufthansa-Basis (Haupteingang)',\n",
        "'U Alter Teichweg|Habichtstraße (Mitte)',\n",
        "'U Wandsbek Markt|Wandsbeker Allee',\n",
        "])]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JMLvDL-2iZpL"
      },
      "source": [
        "data201 =data201.reset_index(drop=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lJihB8vqid7l"
      },
      "source": [
        "route_unique = (data201['Node A to Node B'].unique())\n",
        "route_unique"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fKLwnMayihBx"
      },
      "source": [
        "#act_p = []\n",
        "data201['Actual_trip_cum'] = 0\n",
        "data201['Planned_trip_cum'] = 0\n",
        "a = 0\n",
        "b = 0\n",
        "\n",
        "for i in range(len(data201)):\n",
        "  #print(i)\n",
        "  if data201['Node A to Node B'][i] == route_unique[0]: #the first path\n",
        "    a = data201['Driving_time_s'][i]\n",
        "    data201['Actual_trip_cum'][i] = a\n",
        "    b = data201['Driving_time_s_p'][i]\n",
        "    data201['Planned_trip_cum'][i] = b\n",
        "  else:\n",
        "    a += data201['Driving_time_s'][i] \n",
        "    data201['Actual_trip_cum'][i] = a\n",
        "    b += data201['Driving_time_s_p'][i]\n",
        "    data201['Planned_trip_cum'][i] = b\n",
        "data201.tail() #[:50]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6cKErOf-WUju"
      },
      "source": [
        "#data201.to_csv('ist_0420_data_processed201.csv')\n",
        "#!cp ist_0420_data_processed201.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\"\n",
        "data201.to_csv('ist_01_12_19_data_processed201.csv')\n",
        "!cp ist_01_12_19_data_processed201.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H6MG1KYoWoFl"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GrQKZsNbYxPH"
      },
      "source": [
        "## Journey 202 ***Lufthansa-Basis (Haupteingang) to U Wandsbek Markt***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hBqU-lGnWl4G"
      },
      "source": [
        "df_selected = df_filter.loc[df_filter['S_Station'] == 'Lufthansa-Basis (Haupteingang)'].reset_index()\n",
        "df_selected = df_selected.loc[df_selected['E_Station'] == 'U Wandsbek Markt'].reset_index()\n",
        "df_selected = df_selected[['Ab_ZT_PLAN', 'TagRound', 'UML', 'Linie', 'Node A to Node B', 'Precipitation', 'Driving_time_s_p', 'Driving_time_s']]\n",
        "#df_selected = df_selected.loc[df_selected['UML'] == 77082]\n",
        "df_selected = df_selected.loc[df_selected['Linie']  == 28].reset_index()\n",
        "df_selected = df_selected.loc[(df_selected['Driving_time_s']  <= 1000) & (df_selected['Driving_time_s']  >= 0)].reset_index()\n",
        "df_selected = df_selected.drop(['Linie', 'TagRound', 'index', 'UML', 'level_0'], axis=1)\n",
        "df_selected= df_selected.rename({'Ab_ZT_PLAN': 'Time'}, axis=1)\n",
        "df_selected"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "obytEI8LW1Xv"
      },
      "source": [
        "import math\n",
        "df_selected['dayofweek'] = df_selected['Time'].dt.dayofweek\n",
        "df_selected['hour'] = (df_selected['Time'].dt.hour+1)\n",
        "df_selected['day'] = df_selected['Time'].dt.day\n",
        "df_selected['month'] = df_selected['Time'].dt.month\n",
        "df_selected['timeofday'] = [0 for number in df_selected['Time']]\n",
        "#df_selected"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YpNVFzeJXDXp"
      },
      "source": [
        "Filter Holidays, 19 and 22"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3p4aa23mW_Sx"
      },
      "source": [
        "#df_selected = df_selected[~df_selected['day'].isin([19,22])].reset_index()\n",
        "df_selected = df_selected.loc[~(((df_selected['day'] == 1) & (df_selected['month'] ==  1))\n",
        "                  |((df_selected['day'] == 19) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 21) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 22) & (df_selected['month'] == 4))\n",
        "                  |((df_selected['day'] == 1) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 30) & (df_selected['month'] == 5))\n",
        "                  |((df_selected['day'] == 10) & (df_selected['month'] == 6))\n",
        "                  |((df_selected['day'] == 3) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 31) & (df_selected['month'] == 10))\n",
        "                  |((df_selected['day'] == 25) & (df_selected['month'] == 12))\n",
        "                  |((df_selected['day'] == 26) & (df_selected['month'] == 12))\n",
        "                  ),:].reset_index()\n",
        "#df_selected[:50]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hCYJWnfnXMDP"
      },
      "source": [
        "Find peak hours pattern"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0jHiSirWXJrt"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(df_selected['hour'], df_selected['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('hour', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time on days by hour', fontsize=28)\n",
        "\n",
        "plt.tight_layout()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4KXOxpObXQhz"
      },
      "source": [
        "for i in range(len(df_selected)):\n",
        "  #print('1')\n",
        "  if df_selected['hour'][i]<7:\n",
        "    df_selected['timeofday'][i] = 0\n",
        "  elif df_selected['hour'][i]<11:\n",
        "    df_selected['timeofday'][i] = 1\n",
        "  elif df_selected['hour'][i] < 13:\n",
        "    df_selected['timeofday'][i] = 2\n",
        "  elif df_selected['hour'][i] <19:\n",
        "    df_selected['timeofday'][i] = 3\n",
        "  elif df_selected['hour'][i] <20:\n",
        "    df_selected['timeofday'][i] = 4\n",
        "  else:\n",
        "    df_selected['timeofday'][i] = 5\n",
        "\n",
        "#df_selected\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bRRx0CeIYc_7"
      },
      "source": [
        "df_selected = df_selected.drop(['index','day','hour'], axis=1)\n",
        "#df_selected"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zPec3du4YmHm"
      },
      "source": [
        "len(df_selected['Node A to Node B'].unique())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4LBaKiboBHgy"
      },
      "source": [
        "df_selected.describe()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4HS_nonwBK0R"
      },
      "source": [
        "plt.hist(df_selected['Driving_time_s'])\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y361apxZYqNP"
      },
      "source": [
        "data202 = df_selected.copy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cqPDrarkY_h-"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "\n",
        "plt.plot(data202['Time'], data202['Driving_time_s'], '.', color='red', label='Original data', alpha=0.5)\n",
        "plt.xlabel('Datetime [-]', fontsize=20)\n",
        "plt.ylabel(r'Driving time [s]', fontsize=20)\n",
        "\n",
        "plt.xticks(fontsize=14, rotation=45)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "plt.title('Driving time of line 28 Lufthansa-Basis (Haupteingang) to U Wandsbek Markt', fontsize=28)\n",
        "\n",
        "plt.tight_layout()\n",
        "\n",
        "#plt.savefig('figures/available data.png', dpi=1200)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "74P9EsztiJni"
      },
      "source": [
        "**Add two new columns for accumulate values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SlIPHZYXixcB"
      },
      "source": [
        "data202.loc[data202.Precipitation == -499 ]=0\n",
        "data202 = data202.loc[data202['Node A to Node B'].isin(['Lufthansa-Basis (Haupteingang)|Obenhauptstraße',\n",
        "        'Obenhauptstraße|Alsterkrugchaussee (Mitte)',\n",
        "        'Alsterkrugchaussee (Mitte)|Moltrechtweg',\n",
        "        'Moltrechtweg|Brabandstraße', 'Brabandstraße|Hindenburgstraße',\n",
        "        'Hindenburgstraße|U Alsterdorf', 'U Alsterdorf|Sydneystraße',\n",
        "        'Sydneystraße|Manilabrücke', 'Manilabrücke|Kapstadtring',\n",
        "        'Kapstadtring|S Rübenkamp', 'S Rübenkamp|AK Barmbek', 'AK Barmbek|Hartzloh',\n",
        "        'Hartzloh|Habichtsplatz', 'Habichtsplatz|U Habichtstraße',\n",
        "        'U Habichtstraße|Habichtstraße (Mitte)',\n",
        "        'Habichtstraße (Mitte)|U Alter Teichweg',\n",
        "        'U Alter Teichweg|U Straßburger Straße',\n",
        "        'U Straßburger Straße|Wandsbeker Allee',\n",
        "        'Wandsbeker Allee|U Wandsbek Markt'])]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6T_NvZHqjFiZ"
      },
      "source": [
        "data202 =data202.reset_index(drop=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n_6-F7LLjIez"
      },
      "source": [
        "route_unique = (data202['Node A to Node B'].unique())\n",
        "route_unique"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UbtwcpIBjLY5"
      },
      "source": [
        "#act_p = []\n",
        "data202['Actual_trip_cum'] = 0\n",
        "data202['Planned_trip_cum'] = 0\n",
        "a = 0\n",
        "b = 0\n",
        "\n",
        "for i in range(len(data202)):\n",
        "  #print(i)\n",
        "  if data202['Node A to Node B'][i] == route_unique[0]: #the first path\n",
        "    a = data202['Driving_time_s'][i]\n",
        "    data202['Actual_trip_cum'][i] = a\n",
        "    b = data202['Driving_time_s_p'][i]\n",
        "    data202['Planned_trip_cum'][i] = b\n",
        "  else:\n",
        "    a += data202['Driving_time_s'][i] \n",
        "    data202['Actual_trip_cum'][i] = a\n",
        "    b += data202['Driving_time_s_p'][i]\n",
        "    data202['Planned_trip_cum'][i] = b\n",
        "data202.tail() #[:50]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4QNNSY2yZFtz"
      },
      "source": [
        "#data202.to_csv('ist_0420_data_processed202.csv')\n",
        "#!cp ist_0420_data_processed202.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\"\n",
        "data202.to_csv('ist_01_12_19_data_processed202.csv')\n",
        "!cp ist_01_12_19_data_processed202.csv \"/content/drive/My Drive/Colab Notebooks/Thesis\""
      ],
      "execution_count": 76,
      "outputs": []
    }
  ]
}